空间自适应免疫克隆选择优化算法

针对免疫克隆选择优化算法晚期收敛速度慢的不足，通过引入搜索空间自适应缩放的思想，提出一种新的空间自适应免疫克隆选择优化算法(SAIS)。算法利用不完全演化搜索优化解的分布特性，以精英个体为中心收缩搜索空间，并采用空间扩张机制帮助算法跳出局部最优。通过对高维基准测试函数实验表明，SAIS能显著提高收敛速度和优化解的质量。

Space self-adaptive immune clonal selection optimization algorithm

To improve the convergence speed in standard immune clonal selection algorithm (AIS), a new space self-adaptive immune clonal selection optimization algorithm (SAIS) is presented by introducing the thoughts of space contraction & expansion. The algorithm uses distribute characters of solution in non-complete evolution process to contract searching space, so as to accelerate convergence speed; meanwhile it jumps away from the local optimum by expanding searching space. Four high dimension Benchmark optimization-testing functions were used to study performance of the new optimization algorithm. By Comparison of standard AIS and SAIS, the new algorithm can enhance convergence speed and improve optimization quantity effectively.